Learn data mining through excel: (Record no. 3877)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03108nam a22002057a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20221206154159.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 221206b ||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781484267356 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 004.165 |
| Item number | ZHO |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Zhou, Hong |
| 245 ## - TITLE STATEMENT | |
| Title | Learn data mining through excel: |
| Remainder of title | a step by step approach for understanding machine learning methods |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher, distributor, etc. | Apress |
| Place of publication, distribution, etc. | USA |
| Date of publication, distribution, etc. | 2021 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xvi, 219 p. |
| 365 ## - TRADE PRICE | |
| Price type code | INR |
| Price amount | 799.00 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc. note | Excel and Data Mining<br/>Hong Zhou<br/>Pages 1-19<br/>Linear Regression<br/>Hong Zhou<br/>Pages 21-34<br/>K-Means Clustering<br/>Hong Zhou<br/>Pages 35-47<br/>Linear Discriminant Analysis<br/>Hong Zhou<br/>Pages 49-66<br/>Cross-Validation and ROC<br/>Hong Zhou<br/>Pages 67-81<br/>Logistic Regression<br/>Hong Zhou<br/>Pages 83-92<br/>K-Nearest Neighbors<br/>Hong Zhou<br/>Pages 93-108<br/>Naïve Bayes Classification<br/>Hong Zhou<br/>Pages 109-123<br/>Decision Trees<br/>Hong Zhou<br/>Pages 125-148<br/>Association Analysis<br/>Hong Zhou<br/>Pages 149-161<br/>Artificial Neural Network<br/>Hong Zhou<br/>Pages 163-187<br/>Text Mining<br/>Hong Zhou<br/>Pages 189-209<br/>After Excel |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | About this book<br/>Use popular data mining techniques in Microsoft Excel to better understand machine learning methods.<br/><br/>Software tools and programming language packages take data input and deliver data mining results directly, presenting no insight on working mechanics and creating a chasm between input and output. This is where Excel can help.<br/><br/>Excel allows you to work with data in a transparent manner. When you open an Excel file, data is visible immediately and you can work with it directly. Intermediate results can be examined while you are conducting your mining task, offering a deeper understanding of how data is manipulated and results are obtained. These are critical aspects of the model construction process that are hidden in software tools and programming language packages.<br/><br/>This book teaches you data mining through Excel. You will learn how Excel has an advantage in data mining when the data sets are not too large. It can give you a visual representation of data mining, building confidence in your results. You will go through every step manually, which offers not only an active learning experience, but teaches you how the mining process works and how to find the internal hidden patterns inside the data.<br/><br/><br/><br/>What You Will Learn<br/><br/>Comprehend data mining using a visual step-by-step approach<br/>Build on a theoretical introduction of a data mining method, followed by an Excel implementation<br/>Unveil the mystery behind machine learning algorithms, making a complex topic accessible to everyone<br/>Become skilled in creative uses of Excel formulas and functions<br/>Obtain hands-on experience with data mining and Excel<br/><br/><br/>Who This Book Is For<br/><br/>Anyone who is interested in learning data mining or machine learning, especially data science visual learners and people skilled in Excel, who would like to explore data science topics and/or expand their Excel skills. A basic or beginner level understanding of Excel is recommended. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Microsoft software |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Data mining |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Book |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection code | Bill No | Bill Date | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Cost, normal purchase price | Total Checkouts | Full call number | Accession Number | Date last seen | Copy number | Cost, replacement price | Price effective from | Koha item type |
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| Dewey Decimal Classification | IT & Decisions Sciences | TB2160 | 12-11-2022 | Indian Institute of Management LRC | Indian Institute of Management LRC | General Stacks | 12/07/2022 | Technical Bureau India Pvt. Ltd. | 559.30 | 004.165 ZHO | 003907 | 12/07/2022 | 1 | 799.00 | 12/07/2022 | Book |